Department of Computer Science Seminar
2016 Series

Systems and Algorithms for Big Data Analytics

Dr. Da Yan
Postdoctoral Fellow
The Chinese University of Hong Kong

Date: January 21, 2016 (Thursday)
Time: 10:30 - 11:30 am
Venue: RRS905, Sir Run Run Shaw Building, Ho Sin Hang Campus

We are now in the Big Data era, and scalable techniques for efficient big data analytics are in high demand. This talk introduces the latest development in the field of big data analytics systems, with a special focus on graph processing systems. Google's Pregel is a pioneering distributed framework for big graph analytics, and has inspired numerous researches on big graph systems since its advent in 2010. This talk starts with a brief review on Pregel, and then introduces how to develop graph algorithms for various applications under the model of Pregel with performance guarantees. We then proceed to identify the weaknesses of the existing model of Pregel in processing large real graphs, and introduce a few novel ideas and designs in improving the basic model of Pregel, which often achieve orders of magnitude performance improvements. This talk will cover important topics including computation model, communication mechanism, on-demand querying, out-of-core support, fault tolerance, etc. Many of the introduced works have been published in first-tier conferences, including four recent VLDB papers and one recent WWW paper. The talk will also touch upon the scalable processing of other types of big data such as geo-spatial data and uncertain data, and provide a vision on future directions of big data research.

Dr. YAN, Da is currently a postdoctoral fellow of Computer Science in The Chinese University of Hong Kong. He received his Ph.D. degree in Computer Science from the Hong Kong University of Science and Technology in 2014, and his B.S. degree in Computer Science from Fudan University in Shanghai in 2009. He is the winner of Hong Kong 2015 Young Scientist Award in Physical/Mathematical Science.

Dr. YAN's research focuses on the development of scalable systems and algorithms for big data analytics, with a special emphasis on graph data, geo-spatial data and data uncertainty. The results of his research have been published in top-tier conferences such as SIGKDD, ICDE, EDBT, and top-tier journals such as PVLDB and TKDE. Notably, his first research paper won the best paper award in the 2011 DASFAA conference. His research has been awarded with ITF and GRF grants, and the systems he developed have been used by many research groups as well as companies (e.g., Taobao).

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